In medicine or other fields of interest there may be a need to identify corresponding structures in a plurality of images. In medicine, this task may come up in analyzing images from prior versus follow-up examinations or in analyzing multimodal imagery.
A more specific example where this task frequently occurs is digital breast tomosynthesis (DBT). DBT is an emerging technology in breast imaging where a series of high resolution images of the breast is produced by limited angle tomography. Compared to conventional 2D digital radiography, the amount of image data to be reviewed is significantly higher for “2.5D” tomosynthesis data. Efficient tools for reading and analysis of the tomosynthesis data is therefore desirable, especially in a breast screening setting. To this end, synthetic mammograms have been recently proposed to support efficient reading of tomosynthesis data by an interactive slice selection technique as in Applicant's WO 2013/035026.
Still, finding corresponding image structures can be at times challenging for reasons other than sheer data volume. For instance, in diagnostic breast imaging it may be difficult to identify corresponding lesions acquired at different views such as ipsi-lateral mammographic views taken in the standard cranio-caudal (CC) and medio-lateral oblique (MLO) orientations. Another difficulty in dealing with such multi-view imagery may arise if one wishes to navigate to a certain tomosynthesis slice which one expects to depict more clearly a structure of interest as seen, eg, in a currently displayed synthetic mammogram.